Polynomial joint angle arm robot motion planning in complex geometrical obstacles

This paper addresses a point-to-point of an arm robot motion planning in complex geometrical obstacle. It will govern a two-layer optimization strategy utilizing sixth degree polynomial as joint angle path. At the beginning of the motion planning process, the path planning starts with the optimization objective to minimize the joint angle travelling distance under collision detection rules as constraint. After the best path has been met, the associated time will be searched with the optimization objective to minimize the total travelling time and the torque under the maximum velocity, the maximum acceleration, the maximum jerk, and the maximum torque constraints. The performance of a Genetic Algorithm (GA) and a Particle Swarm Optimization (PSO) will be investigated in searching the feasible sixth degree polynomial joint angle path and the total travelling time that gives the optimal trajectories under kinodynamic constraints. A 3-Degree-Of-Freedom (3-DOF) planar robot will be utilized to simulate the proposed scenario.

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► Finding the feasible motion of the robotic arm at complex geometrical obstacle.
► Generating the polynomial joint angle directly in the joint space.
► Considering both kinematics and dynamics constraints.
► Exploring the searching ability of the computational method to find the unknown feasible zone.
► It does not need to do mapping from the Cartesian space to the joint space.